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The urban.NET
The cities and communities ....the present and the future - urban change.NET -
Curated by luiy
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My City – Crowdsourced #urban planning platform | #Participatory #democracy

My City – Crowdsourced #urban planning platform | #Participatory #democracy | The urban.NET |
luiy's insight:

Collect ideas on improving your city


My City is a platform for sharing and discussing ideas on what can be improved in the city and how to make it happen.



Inspire people to take action


The platform lets users update the status of proposals, helping them feel engaged in the whole process of implementation.

bart rosseau's curator insight, June 5, 2014 3:19 AM

a fine example of crowdsource platforms...

Rescooped by luiy from visual data!

Datascaping And Designing With Information | #dataviz #urbanism

Datascaping And Designing With Information | #dataviz #urbanism | The urban.NET |

DataAppeal software provides an alternative to complex mapping tools through an easy to use, web-based GIS application that renders typical data files into beautifully designed multi-dimensional maps and datascapes instantly. For architects, landscape architects, urban planners and designers of the built form, the application is a great tool to utilize evidence-based information to expose new site patterns, to provide alternative 3D modes of mapping for communication purposes, and to aid in the initiation of master plan designs.

It’s also a refreshing way to visually engage professional and students with their site-based data...

Via Lauren Moss
burlysand's comment, September 24, 2013 3:28 AM
Pretty simple..
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"Natural #Cities" Emerge from Social Media Location #Data | #context #planing

"Natural #Cities" Emerge from Social Media Location #Data | #context #planing | The urban.NET |
Nobody agrees on how to define a city. But the emergence of “natural cities” from social media data sets may change that, say computational geographers.
luiy's insight:

Jiang and Miao began with a dataset from the Brightkite social network, which was active between 2008 and 2010. The site encouraged users to log in with their location details so that they could see other users nearby. So the dataset consists of almost 3 million locations in the US and the dates on which they were logged.

To start off, Jiang and Miao simply placed a dot on a map at the location of each login. They then connected these dots to their neighbours to form triangles that end up covering the entire mainland US.


Next, they calculated the size of each triangle on the map and plotted this size distribution, which turns out to follow a power law. So there are lots of tiny triangles but only a few large ones.


Finally, the calculated the average size of the triangles and then coloured in all those that were smaller than average. The coloured areas are “natural cities”, say Jiang and Miao.

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